Comparing tuberculosis gene signatures in malnourished individuals using the TBSignatureProfiler

Abstract

Background Gene expression signatures have been used as biomarkers of tuberculosis (TB) risk and outcomes. Platforms are needed to simplify access to these signatures and determine their validity in the setting of comorbidities. We developed a computational profiling platform of TB signature gene sets and characterized the diagnostic ability of existing signature gene sets to differentiate active TB from LTBI in the setting of malnutrition. Methods We curated 45 existing TB-related signature gene sets and developed our TBSignatureProfiler software toolkit that estimates gene set activity using multiple enrichment methods and allows visualization of single- and multi-pathway results. The TBSignatureProfiler software is available through Bioconductor and on GitHub. For evaluation in malnutrition, we used whole blood gene expression profiling from 23 severely malnourished Indian individuals with TB and 15 severely malnourished household contacts with latent TB infection (LTBI). Severe malnutrition was defined as body mass index (BMI) < 16 kg/m2 in adults and based on weight-for-height Z scores in children < 18 years. Gene expression was measured using RNA-sequencing. Results The comparison and visualization functions from the TBSignatureProfiler showed that TB gene sets performed well in malnourished individuals; 40 gene sets had statistically significant discriminative power for differentiating TB from LTBI, with area under the curve ranging from 0.662–0.989. Three gene sets were not significantly predictive. Conclusion Our TBSignatureProfiler is a highly effective and user-friendly platform for applying and comparing published TB signature gene sets. Using this platform, we found that existing gene sets for TB function effectively in the setting of malnutrition, although differences in gene set applicability exist. RNA-sequencing gene sets should consider comorbidities and potential effects on diagnostic performance.

Malnutrition leads to increased inflammation and expression of tuberculosis risk signatures in recently exposed household contacts of pulmonary tuberculosis

“…The TBSignatureProfiler was used to profile signatures; it contains functions for analyzing gene lists from pathways or signatures to determine the predictive value ( 24 ). Scoring methods used here were Gene Set Variance Analysis (GSVA) and single sample Gene Set Enrichment Analysis (ssGSEA).…”

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis

“…To assess the significance of the 12-marker signature in independent TB cohorts, we performed ssGSEA on published transcriptomic TB datasets 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 from the curated TBData R package ( Table S1 ). We observed higher enrichment scores in the active TB group, compared with either latent TB or healthy controls in all the transcriptomic TB datasets except one (GEO: GSE19444 ) ( Figure 4 A).…”

“…We compared the 12-marker signature with the other published gene signatures 12 , 28 , 29 , 32 , 33 , 34 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 from the TBSignatureProfiler R package 36 and published protein signatures 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 to investigate the overlap with the proteins of our signature ( Figure 4 C). VEGFA, IL-6, and IFN-gamma were identified in at least 2 other proteomic studies, 58 , 59 , 60 , 61 , 62 whereas CD274 (also called PD-L1) was observed in several published transcriptional signatures.…”

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis

“…We then compared the 12-marker signature with the other published gene signatures from the TBSignatureProfiler R package (28) and published protein signatures to investigate overlap between protein and transcriptional signatures with the proteins of our signature (Figure 5C). VEGFA, IL6, and IFN-gamma were identified in at least two other proteomic studies (29)(30)(31)(32)(33), while CD274 (also called PD-L1) was observed in several published transcriptional signatures.…”